Sea Level Rise 2020 - 2050 in Foster City
Bella Raja in collaboration with Merrick and Awoe
2/17/2022
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## layout##Sea Level Rise and Flooding in Foster City The Stanford Urban Risk Framework (SURF) analyzes risk estimation given hazard, exposure, and vulnerability data. I assess Foster City’s risk with Sea Level Rise and occurrence of flooding through the lens of SURF.
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|======================================================================| 100%Map of a Test Flood in Foster City 
This map shows how a test flood would impact Foster City’s geography.
Test Flood Depth Map
## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
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## treated as NAThis map shows a test flood scenario in Foster City. If you zoom in, you can see the inland flooding areas due to the canal waterways throughout the city. This is a unique feature of Foster City’s vulnerability when it comes to flooding and sea level rise.
Next, I will loop through San Mateo County sea level rise data to create 9 different sea level rise maps and later 15 different scenarios. These scenarios will help predict sea level rise and flood occurrence from 2020 to 2050.
## [1] "SLR000_RP001"
## [1] "SLR000_RP020"
## [1] "SLR000_RP100"
## [1] "SLR025_RP001"
## [1] "SLR025_RP020"
## [1] "SLR025_RP100"
## [1] "SLR050_RP001"
## [1] "SLR050_RP020"
## [1] "SLR050_RP100"## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
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## +wktext +no_defs +type=crs## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
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## +wktext +no_defs +type=crs## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
## prefer_proj): Discarded datum World Geodetic System 1984 in Proj4 definition## Warning in colors(.): Some values were outside the color scale and will be
## treated as NAThis map shows the maximum flooding in Foster City from the worst of the 9 scenarios.
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## geometries of x## Joining, by = "GEOID20"## Joining, by = "osm_id"Vulnerability
This next section will tackle vulnerability to sea level rise and flooding in Foster City, in particular assessing damages to vehicles and buildings.
Building & Vehicle Exposure & Vulnerability
## Joining, by = c("osm_id", "SLR", "RP")This plot shows the flood depth and percent of building damage in Foster City for a 100 year storm. A flood depth of 0 represents about a first floor elevation of a building.
As we can see, the more flood depth, the higher the percent damage will be. Negative depth can also damage the structure and lower levels of a building. With Sea Level Rise, the flood depth only increases. After about 6 feet of flood depth, there is about 100% damage to buildings, which is a frightening prospect for Foster City.
## Joining, by = c("osm_id", "SLR", "RP")This plot shows vehicle damages on the same timeline as that of the building damages. As you can see when you press play on the Sea Level Rise (SLR), vehicles will be damaged at a much higher rate than buildings. Assuming that they are all on the ground-level, vehicles are much more exposed than higher levels of buildings and are more vulnerable to damage at lower depths of flooding. Despite the different initial rates of increase, after about 6 feet of flooding this estimate also puts vehicles close to 100% damage as well as buildings.
This interactive plot shows the building damage along with storm severity with 50 cm of Sea Level Rise. Vehicles have a higher initial rate of damage than the buildings (shown above). This again emphasizes the increased exposure of vehicles to risk in storms with Sea Level Rise.
Risk Estimation
In this next section, different hazard scenarios will be set and assessed for the risks they pose and their potential exceedance rates.
`
Average Annualized Loss from Sea Level Rise
Buildings
## Rows: 10 Columns: 10## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (10): SLR, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100##
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## SLR `2020` `2030` `2040` `2050` `2060` `2070` `2080` `2090` `2100`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0 0.942 0.923 0.793 0.508 0.235 0.094 0.033 0.011 0.005
## 2 25 0 0.051 0.198 0.453 0.581 0.44 0.249 0.128 0.071
## 3 50 0 0 0.001 0.035 0.176 0.363 0.409 0.313 0.19
## 4 75 0 0 0 0 0.007 0.099 0.224 0.296 0.29
## 5 100 0 0 0 0 0 0.004 0.075 0.162 0.219
## 6 125 0 0 0 0 0 0 0.01 0.064 0.126
## 7 150 0 0 0 0 0 0 0 0.025 0.055
## 8 175 0 0 0 0 0 0 0 0.001 0.034
## 9 200 0 0 0 0 0 0 0 0 0.01
## 10 500 0 0 0 0 0 0 0 0 0## Joining, by = "osm_id"## Joining, by = "SLR"## # A tibble: 6 × 3
## osm_id year damage
## <chr> <chr> <dbl>
## 1 23656875 2020 23262.
## 2 23656875 2030 62192.
## 3 23656875 2040 174039.
## 4 23656875 2050 414848.
## 5 30932783 2020 0
## 6 30932783 2030 0#Vehicles
## Joining, by = "SLR"Average Annualized Loss for Vehicles from 2020-2050
This plot shows the average annualized damages from 2020 to 2050 in the OSM ID areas in Foster City.
Using EMFAC data and projection, we can also compare how many vehicles there will be in Foster City over time and use this in the analysis of vehicle damages due to sea level rise and flooding.
## # A tibble: 4 × 3
## year vehic_count perc_incr
## <chr> <dbl> <dbl>
## 1 2020 490878. 1
## 2 2030 695892. 1.42
## 3 2040 827011. 1.68
## 4 2050 883185. 1.80This table shows the vehicle count and percent increase in Foster City over time based on EMFAC projections. We can see the vehicle count going up about 392,308 cars from 2020 to 2050 which will mean more vehicles that will be damaged with Sea Level Rise in 2050.
## Joining, by = "osm_id"## Joining, by = "year"## Joining, by = "osm_id"AAL in Foster City Buildings 2020 - 2050
This map shows the average annualized loss due to sea level rise and flooding in Foster City Buildings. You can also see the difference between the 2020 and 2050 scenario by clicking on the ‘change’ option.
Vehicle Damage per Building
## Joining, by = "osm_id"Average Annualized Loss for Vehicles in Foster City from 2020-2050
## Warning in st_centroid.sf(.): st_centroid assumes attributes are constant over
## geometries of x## Joining, by = "osm_id"## Joining, by = "GEOID"## Warning: sf layer has inconsistent datum (+proj=longlat +datum=NAD83 +no_defs).
## Need '+proj=longlat +datum=WGS84'Foster City Vehicle and Building Demographics Another aspect of vulnerability to consider is the households experiencing poverty in Foster City.
Households Below the Poverty Line in Foster City Block Groups
| Census Block Group | Total Households | Households below the Poverty Line | Percent below Poverty Line |
|---|---|---|---|
| 060816080011 | 644 | 0 | 0.00000 |
| 060816080012 | 456 | 79 | 17.32456 |
In these Foster City Block groups, one has zero % of households below the poverty line whereas the other has 17%. Especially when considering where sea level rise hits the most, economic vulnerability is highly linked to risk. Additionally, many communities experiencing poverty are often concentrated in areas in which sea level rise will be the highest and various hazards already exist.
Foster City Vehicle Ownership By Tenure
## `summarise()` has grouped output by 'cbg'. You can override using the `.groups` argument.| cbg | tenure | Total Vehicle Count | No vehicle available | 1 vehicle available |
|---|---|---|---|---|
| 060816080011 | Owner occupied: | 1357 | 0 | 187 |
| 060816080011 | Renter occupied: | 275 | 0 | 89 |
| 060816080012 | Owner occupied: | 22 | 9 | 0 |
| 060816080012 | Renter occupied: | 908 | 38 | 360 |
For each cbg in Foster City you can see in the table the total vehicle count for each tenure of resident. Looking more deeply into the data we can also examine which households have no vehicles or just 1 vehicle available to use. Most households that are renter occupied have higher occurrences of having 1 or no vehicles available to them. Renters are often lower income which further compounds the vulnerability of these households in the event of a flood and with sea level rise. When damages are accrued for that one vehicle, it will impact mobility and financial security for those households.
Overall, it is also important to understand the values and limitations of these predictions determined by EMFAC and my data analysis. How scientists determine risk and calculate damages is often different. It is also important to examine how far out into the future our analyses will be accurate or relevant. For Foster City in particular, there is a lot of vulnerability, exposure, and risk with imminent Sea Level Rise and flooding from 2020 and 2050. Hopefully, policy makers, community stakeholders, and local organizations can collaborate to identify areas with the highest vulnerabilities to target for flood mitigation.